HP HPE2-T38 : HPE AI and Machine Learning

  • Exam Code: HPE2-T38
  • Exam Name: HPE AI and Machine Learning
  • Updated: Aug 02, 2026     Q & A: 108 Questions and Answers

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HP HPE2-T38 Exam Syllabus Topics:

SectionWeightObjectives
Articulate the Business Value of HPE ML Solutions24%- Business value and positioning
  • 1. Benefits of Machine Learning Development Management System
  • 2. Benefits of Machine Learning Development Environment
  • 3. HPE AI market positioning
Engage with Customers10%- Customer engagement and proof of concept
  • 1. Identifying engagement personas
  • 2. Qualifying customers for HPE AI offerings
  • 3. Running proof-of-concept demonstrations
Understand Machine Learning Ecosystem Fundamentals13%- Machine learning technology fundamentals
  • 1. Challenges in deep learning model training
  • 2. Machine learning and deep learning concepts
  • 3. Components of machine learning ecosystems
Demonstrate and Explain How to Use HPE Machine Learning PDK18%- Using HPE ML PDK
  • 1. Model deployment
  • 2. Automation and integration workflows
  • 3. Data versioning and lineage
  • 4. Training machine learning models
Compare HPE ML Enterprise Offerings to Open-Source Versions7%- Enterprise vs open-source comparison
  • 1. Enterprise features and advantages
  • 2. Scalability and management capabilities
Examine HPE Machine Learning Offerings15%- HPE AI and ML portfolio
  • 1. Capabilities of HPE AI-at-scale portfolio
  • 2. Aligning HPE ML solutions to customer goals
  • 3. HPE machine learning deployment solutions
Describe Requirements and Prerequisites for HPE ML Solutions13%- Architecture and deployment
  • 1. Infrastructure requirements
  • 2. Deployment options
  • 3. HPE machine learning architecture

HPE AI and Machine Learning Sample Questions:

1. In ML, ''feature selection'' is important for:
Response:

A) Reducing computational requirements
B) All of the above
C) Improving model interpretability
D) Enhancing data storage efficiency


2. Adequate data storage is necessary for machine learning. This storage should be:
Response:

A) Limited to cloud storage only
B) Restricted to local storage only
C) Scalable to handle large datasets
D) Minimal, as ML models require little data


3. The main purpose of HPE Machine Learning Data Management Software is to:
Response:

A) Manage online retail platforms
B) Provide gaming solutions
C) Accelerate ML model production
D) Automate customer support


4. For large-scale machine learning solutions, what type of data handling capability is essential?
Response:

A) Capability to process and analyze large, dynamic datasets
B) The ability to process data is not important
C) Only cloud-based data handling is required
D) Ability to handle small, static datasets only


5. What distinguishes the documentation and learning resources of HPE Machine Learning solutions from open-source versions?
Response:

A) Both are equally lacking in documentation
B) Open-source versions provide better documentation
C) Documentation is not available for either
D) HPE offers more comprehensive and structured documentation


Solutions:

Question # 1
Answer: B
Question # 2
Answer: C
Question # 3
Answer: C
Question # 4
Answer: A
Question # 5
Answer: D

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